The project is based on Window10+Python3.6 environment, and uses Python libraries such as OpenCV, Sklearn and PyQt5 to construct a relatively complete gesture recognition and translation system, which can recognize all kinds of static gesture signals in life, and translate them into Chinese or Arabic numerals through image processing.Due to the limitation of the training amount of Support Vector Machines (SVM), this design is only used to recognize gesture actions 1-10, and the interface is designed using PyQt5 for real-time display of the results of gesture recognition translation.The paper focuses on the noise elimination, contour extraction, RGB colorspace and YCrCb feasibility comparison of still images of 1-10 gesture features extracted by computer camera, GUI page design, Fourier operator extraction of gestures, training SVM model, and debugging of the system. The system is also able to be integrated on different development boards and can be embedded in device carriers to meet multi-scene adaptability.
{"title":"Design of gesture recognition system based on machine vision","authors":"Weiquan Chen, Jichao Yan, Shufen Huang, L.G. Tan","doi":"10.1117/12.2667314","DOIUrl":"https://doi.org/10.1117/12.2667314","url":null,"abstract":"The project is based on Window10+Python3.6 environment, and uses Python libraries such as OpenCV, Sklearn and PyQt5 to construct a relatively complete gesture recognition and translation system, which can recognize all kinds of static gesture signals in life, and translate them into Chinese or Arabic numerals through image processing.Due to the limitation of the training amount of Support Vector Machines (SVM), this design is only used to recognize gesture actions 1-10, and the interface is designed using PyQt5 for real-time display of the results of gesture recognition translation.The paper focuses on the noise elimination, contour extraction, RGB colorspace and YCrCb feasibility comparison of still images of 1-10 gesture features extracted by computer camera, GUI page design, Fourier operator extraction of gestures, training SVM model, and debugging of the system. The system is also able to be integrated on different development boards and can be embedded in device carriers to meet multi-scene adaptability.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126328988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Brain-computer interface (BCI) is a link between the human brain and a computer or other peripheral devices for communication and control. The most frequently utilized BCI paradigms at the time are motor imagination (MI) BCI. In the procedure of MI-BCI, one of the most important roles is the feature extraction of EEG signals. This article examines various feature extraction approaches in four distinct domains: time, frequency, time-frequency, and spatial. Various approaches are introduced in each domain, including the ERD/ERS computation, the FFT method, the Wavelet Transform (WT), the Discrete Wavelet Transform (DWT), Common Spatial Patterns (CSP), and Sub-band Common Spatial Patterns (SBCSP). This paper also compares the advantages and disadvantages of different methods in practical application, which can provide reference for future research.
{"title":"EEG feature extraction methods in motor imagery brain computer interface","authors":"Fengge Bao, Weiheng Liu","doi":"10.1117/12.2667875","DOIUrl":"https://doi.org/10.1117/12.2667875","url":null,"abstract":"Brain-computer interface (BCI) is a link between the human brain and a computer or other peripheral devices for communication and control. The most frequently utilized BCI paradigms at the time are motor imagination (MI) BCI. In the procedure of MI-BCI, one of the most important roles is the feature extraction of EEG signals. This article examines various feature extraction approaches in four distinct domains: time, frequency, time-frequency, and spatial. Various approaches are introduced in each domain, including the ERD/ERS computation, the FFT method, the Wavelet Transform (WT), the Discrete Wavelet Transform (DWT), Common Spatial Patterns (CSP), and Sub-band Common Spatial Patterns (SBCSP). This paper also compares the advantages and disadvantages of different methods in practical application, which can provide reference for future research.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128322068","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zilin Zeng, Junwei Wang, Zhigang Hu, Dongnan Su, Peng Shang
In this paper, a novel policy network update approach based on Proximal Policy Optimization (PPO), Advantageous Update Policy Proximal Policy Optimization (AUP-PPO), is proposed to alleviate the problem of over-fitting caused by the use of shared layers for policy and value functions. Extended from the previous sample-efficient reinforcement learning method PPO that uses separate networks to learn policy and value functions to make them decouple optimization, AUP-PPO uses the value function to calculate the advantage and updates the policy with the loss between the current and target advantage function as a penalty term instead of the value function. Evaluated by multiple benchmark control tasks in Open-AI gym, AUP-PPO exhibits better generalization to the environment and achieves faster convergence and better robustness compared with the original PPO.
{"title":"Advantage policy update based on proximal policy optimization","authors":"Zilin Zeng, Junwei Wang, Zhigang Hu, Dongnan Su, Peng Shang","doi":"10.1117/12.2667235","DOIUrl":"https://doi.org/10.1117/12.2667235","url":null,"abstract":"In this paper, a novel policy network update approach based on Proximal Policy Optimization (PPO), Advantageous Update Policy Proximal Policy Optimization (AUP-PPO), is proposed to alleviate the problem of over-fitting caused by the use of shared layers for policy and value functions. Extended from the previous sample-efficient reinforcement learning method PPO that uses separate networks to learn policy and value functions to make them decouple optimization, AUP-PPO uses the value function to calculate the advantage and updates the policy with the loss between the current and target advantage function as a penalty term instead of the value function. Evaluated by multiple benchmark control tasks in Open-AI gym, AUP-PPO exhibits better generalization to the environment and achieves faster convergence and better robustness compared with the original PPO.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131033673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yu Liu, Zhiqiang Wang, Fengjing Zhang, Jun Xie, Zhaohong Xu
In order to obtain the scale information of ship targets effectively, we proposed an improved Faster R-CNN algorithm which integrated multi-scale region proposal and pooling of ROI, visual attention mechanism and rotation region regression and suppression, and ship targets can be positioned by the rotate quadrangle bounding boxes to obtain the scale information of them. Our improved model is based on the standard Faster R-CNN and is maintained through end-to-end training.
{"title":"Target scale information detection based on improved Faster R-CNN","authors":"Yu Liu, Zhiqiang Wang, Fengjing Zhang, Jun Xie, Zhaohong Xu","doi":"10.1117/12.2667260","DOIUrl":"https://doi.org/10.1117/12.2667260","url":null,"abstract":"In order to obtain the scale information of ship targets effectively, we proposed an improved Faster R-CNN algorithm which integrated multi-scale region proposal and pooling of ROI, visual attention mechanism and rotation region regression and suppression, and ship targets can be positioned by the rotate quadrangle bounding boxes to obtain the scale information of them. Our improved model is based on the standard Faster R-CNN and is maintained through end-to-end training.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132126119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The essence of enjoying music is that people can track music beat anytime and be brought into the scene expressed by music. Music beat tracking is a common task in Music Information Retrieve (MIR). While numerous studies have been done in this field, most works focus on the offline beat tracking. However, tracking music beat in real time is a challenging task for computers. In the past few years, people attach more importance to this field. Researchers care about the music beat without taking music style or context into consideration. In this paper, we propose a method for tracking music beats in real time in conjunction with music genre. Specifically, the proposed model is based on a widely-used framework of Hidden Markov Model (HMM). By recognizing the genre of input music, we narrow the range of beats per minute (BPM), which significantly reduces the number of hidden states in HMM. Consequently, the inference time of beat tracking decreases. We experimentally verify the model on the open-source Ballroom dataset, and its accuracy remains at a competitive level while having a much shorter inference time.
{"title":"Accelerating real-time music beat tracking based on hidden Markov model by using genre information","authors":"Liangfeng Zhou, Guangxiao Song, Zhi-jian Wang, Meng Xia","doi":"10.1117/12.2667472","DOIUrl":"https://doi.org/10.1117/12.2667472","url":null,"abstract":"The essence of enjoying music is that people can track music beat anytime and be brought into the scene expressed by music. Music beat tracking is a common task in Music Information Retrieve (MIR). While numerous studies have been done in this field, most works focus on the offline beat tracking. However, tracking music beat in real time is a challenging task for computers. In the past few years, people attach more importance to this field. Researchers care about the music beat without taking music style or context into consideration. In this paper, we propose a method for tracking music beats in real time in conjunction with music genre. Specifically, the proposed model is based on a widely-used framework of Hidden Markov Model (HMM). By recognizing the genre of input music, we narrow the range of beats per minute (BPM), which significantly reduces the number of hidden states in HMM. Consequently, the inference time of beat tracking decreases. We experimentally verify the model on the open-source Ballroom dataset, and its accuracy remains at a competitive level while having a much shorter inference time.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134433792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the increase in energy demand, carbon emissions, environmental pollution, climate change and other issues have become increasingly prominent, China has accelerated the construction of new energy sources. Especially in the field of wind power generation, it is the most potential type of large-scale development of non-hydroelectric renewable energy. Due to the volatility, intermittency and low energy density of wind power, the power of wind power also fluctuates. However, with the early digital transformation of my country's energy industry, a large number of meteorological environments and equipment measurement points have been accumulated in wind power production sites. Power generation related data, using artificial intelligence, deep learning and other technologies can effectively predict the power generation of the station with high precision. A model algorithm of multi-loop gradient boosting decision tree is used in this paper, considering the stationarity test of time series and wind power fluctuation attribute, the accuracy of wind power prediction is effectively improved. Help the power dispatching department to pre-arrange dispatching plans according to wind power changes. Ensure the smooth and safe operation of the power grid.
{"title":"Wind power prediction method based on multi-loop improved gradient boosting decision tree","authors":"Zheng He, Lin Xu, Yufei Ai, Wei Li, Huanhuan Dong","doi":"10.1117/12.2667668","DOIUrl":"https://doi.org/10.1117/12.2667668","url":null,"abstract":"With the increase in energy demand, carbon emissions, environmental pollution, climate change and other issues have become increasingly prominent, China has accelerated the construction of new energy sources. Especially in the field of wind power generation, it is the most potential type of large-scale development of non-hydroelectric renewable energy. Due to the volatility, intermittency and low energy density of wind power, the power of wind power also fluctuates. However, with the early digital transformation of my country's energy industry, a large number of meteorological environments and equipment measurement points have been accumulated in wind power production sites. Power generation related data, using artificial intelligence, deep learning and other technologies can effectively predict the power generation of the station with high precision. A model algorithm of multi-loop gradient boosting decision tree is used in this paper, considering the stationarity test of time series and wind power fluctuation attribute, the accuracy of wind power prediction is effectively improved. Help the power dispatching department to pre-arrange dispatching plans according to wind power changes. Ensure the smooth and safe operation of the power grid.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131574864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
For the rail traffic, feasibility of 5th Generation (5G) mobile communication massive Multiple Input Multiple Output (MIMO) used in the tunnel is studying. In order to effectively set up base station, antenna and intelligent reflecting surface (IRS), the direction of arrival (DOA) must be captured. Aiming at the problem of poor performance of two-dimensional MUltiple SIgnal Classification (2D-MUSIC) algorithm in the environment of low signal-to-noise ratio (SNR), small snapshots and small incident angle interval signals, an improved MUSIC algorithm with uniform rectangular array (URA) based on reconstructive subspace is proposed. By reconstructing subspace, a new spatial spectrum is obtained in terms of subspace eigenvectors. Then, the DOAs are obtained by searching the maximum of the new spatial spectrum. High estimation accuracy and angular resolution are often required in practical applications of rail traffic 5G system, and there exist tunnel scenarios that we need the improved MUSIC algorithm has the ability to conduct two-dimensional DOA estimation. Simulations and the measured data of straight tunnel scenario are used to verify the effectiveness of the proposed algorithm and its higher searching precision in complex signal environments such as low SNR, strong-to-weak proximity, and coherent interference.
{"title":"DOA estimation of rail transit tunnel far field signals based on reconstructive subspace MUSIC","authors":"Yanliang Jin, Rukun Lyu, Yuan Gao, Guoxing Zheng","doi":"10.1117/12.2667279","DOIUrl":"https://doi.org/10.1117/12.2667279","url":null,"abstract":"For the rail traffic, feasibility of 5th Generation (5G) mobile communication massive Multiple Input Multiple Output (MIMO) used in the tunnel is studying. In order to effectively set up base station, antenna and intelligent reflecting surface (IRS), the direction of arrival (DOA) must be captured. Aiming at the problem of poor performance of two-dimensional MUltiple SIgnal Classification (2D-MUSIC) algorithm in the environment of low signal-to-noise ratio (SNR), small snapshots and small incident angle interval signals, an improved MUSIC algorithm with uniform rectangular array (URA) based on reconstructive subspace is proposed. By reconstructing subspace, a new spatial spectrum is obtained in terms of subspace eigenvectors. Then, the DOAs are obtained by searching the maximum of the new spatial spectrum. High estimation accuracy and angular resolution are often required in practical applications of rail traffic 5G system, and there exist tunnel scenarios that we need the improved MUSIC algorithm has the ability to conduct two-dimensional DOA estimation. Simulations and the measured data of straight tunnel scenario are used to verify the effectiveness of the proposed algorithm and its higher searching precision in complex signal environments such as low SNR, strong-to-weak proximity, and coherent interference.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132144386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To improve the accuracy of the power supply enterprise service network public opinion crisis early warning, the fuzzy reasoning theory is introduced to carry out the design research of the power supply enterprise service network public opinion early warning method. Based on public opinion topic intensity, development heat and public attitude, the power supply enterprise service network public opinion early warning index system is constructed. Combined with fuzzy reasoning theory, the index membership degree and early warning level membership degree are calculated. Through the learning method, the public opinion early warning level judgment rule is learned, and the public opinion early warning level judgment and early warning display are completed. The experiment proves that the new public opinion early warning method can accurately judge the degree of public opinion crisis, and give a reasonable and intuitive early warning display result.
{"title":"Early warning method of power supply enterprise service network public opinion based on fuzzy reasoning","authors":"Qianqian Li, Wenjie Fan, Xiaozhou Shen, Jing Li","doi":"10.1117/12.2667502","DOIUrl":"https://doi.org/10.1117/12.2667502","url":null,"abstract":"To improve the accuracy of the power supply enterprise service network public opinion crisis early warning, the fuzzy reasoning theory is introduced to carry out the design research of the power supply enterprise service network public opinion early warning method. Based on public opinion topic intensity, development heat and public attitude, the power supply enterprise service network public opinion early warning index system is constructed. Combined with fuzzy reasoning theory, the index membership degree and early warning level membership degree are calculated. Through the learning method, the public opinion early warning level judgment rule is learned, and the public opinion early warning level judgment and early warning display are completed. The experiment proves that the new public opinion early warning method can accurately judge the degree of public opinion crisis, and give a reasonable and intuitive early warning display result.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121600613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Micro air-launched decoy (MALD) is electronic weapon aiming to interfere with enemy air defense systems. MALD uses signal enhancement subsystems and active radar jammers as its loads. This paper discusses the basic situation of MALD in detail, and analyzes the technical advantages and development trends.
{"title":"Technology research of micro air-launched decoy","authors":"Fang-zheng Zhao, Xiao Zhang, Xin Zhang","doi":"10.1117/12.2667665","DOIUrl":"https://doi.org/10.1117/12.2667665","url":null,"abstract":"Micro air-launched decoy (MALD) is electronic weapon aiming to interfere with enemy air defense systems. MALD uses signal enhancement subsystems and active radar jammers as its loads. This paper discusses the basic situation of MALD in detail, and analyzes the technical advantages and development trends.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121179015","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the new operational styles such as mosaic warfare and multi-domain warfare of the US military moving from concept to application, the winning elements and operational modes of future maritime operations have been profoundly changed. Firstly, the military capabilities of the US military to break through anti-access/area denial are analyzed, and then the characteristics and effects of the implementation of multi-domain warfare under the mosaic warfare concept in breaking through anti-access/area denial are extracted from the military capabilities, operational styles, and practical applications. On this basis, countermeasure suggestions are proposed to deal with the implementation of multi-domain warfare under the mosaic warfare concept. The practical significance of building unmanned maritime combat clusters is explained from the perspective of military needs, and the force design, equipment development, and combat style of unmanned maritime combat clusters are described in detail. A typical combat scenario is used to show the combat process of unmanned maritime combat clusters. Finally, the key problem model of intelligent command and control decision of maritime unmanned cluster is established for this typical combat scenario, and the corresponding algorithmic framework is constructed for the input and output of the typical combat scenario, which provides research ideas for further empirical research.
{"title":"Analysis of maritime unmanned combat cluster employment in the context of anti-intervention/area denial","authors":"Jiangshan Liu, P. Pen","doi":"10.1117/12.2667516","DOIUrl":"https://doi.org/10.1117/12.2667516","url":null,"abstract":"With the new operational styles such as mosaic warfare and multi-domain warfare of the US military moving from concept to application, the winning elements and operational modes of future maritime operations have been profoundly changed. Firstly, the military capabilities of the US military to break through anti-access/area denial are analyzed, and then the characteristics and effects of the implementation of multi-domain warfare under the mosaic warfare concept in breaking through anti-access/area denial are extracted from the military capabilities, operational styles, and practical applications. On this basis, countermeasure suggestions are proposed to deal with the implementation of multi-domain warfare under the mosaic warfare concept. The practical significance of building unmanned maritime combat clusters is explained from the perspective of military needs, and the force design, equipment development, and combat style of unmanned maritime combat clusters are described in detail. A typical combat scenario is used to show the combat process of unmanned maritime combat clusters. Finally, the key problem model of intelligent command and control decision of maritime unmanned cluster is established for this typical combat scenario, and the corresponding algorithmic framework is constructed for the input and output of the typical combat scenario, which provides research ideas for further empirical research.","PeriodicalId":128051,"journal":{"name":"Third International Seminar on Artificial Intelligence, Networking, and Information Technology","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127893662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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